如何在本地部署DeepSeek大模型实现联网增强的AI应用

var endpoint = new Uri("http://你的ollama地址:11434");
var modelId = "deepseek-r1:14b";
var builder = Kernel.CreateBuilder();
builder.AddOllamaChatCompletion(modelId, endpoint);

public class SearchSkill
{
    // 执行搜索并处理结果
    public async Task<List<SearchResult>> SearchAsync(string query)
    {
        // 构建请求参数
        var parameters = new Dictionary<string, string> {
            { "q", query },
            { "format", "json" },
            // ...其他参数
        };
        // 处理响应并解析
        var jsonResponse = await response.Content.ReadAsStringAsync();
        return ProcessResults(jsonResponse);
    }
}

// 初始化服务
var kernel = builder.Build();
var chatService = kernel.GetRequiredService<IChatCompletionService>();
var searchService = kernel.GetRequiredService<SearchSkill>();
// 执行搜索
List<SearchResult> result = await searchService.SearchAsync(query);
// 构建提示词
var chatHistory = new ChatHistory();
chatHistory.AddSystemMessage($"找到{result.Count}条结果：");
// ...添加搜索结果
// 获取模型响应
await foreach (var item in chatService.GetStreamingChatMessageContentsAsync(chatHistory))
{
    Console.Write(item.Content);
}

var sortedResults = results.OrderByDescending(r => r.Score);

private List<Result> FilterResults(...)